Research on the Current Situation, Advantages, and Challenges of Blended Learning Models in Higher Vocational Colleges
Bin Xiao
School of Information Engineering, Guangzhou Vocational College of Technology & Business, Guangzhou, China
Jialong Chen
School of Information Engineering, Guangzhou Vocational College of Technology & Business, Guangzhou, China
Weijun He
School of Information Engineering, Guangzhou Vocational College of Technology & Business, Guangzhou, China
ABSTRACT:
With the rapid development of information technology, blended learning models have been widely adopted in higher vocational colleges. This paper aims to explore the current status of online and offline blended learning in higher vocational colleges, analyze its advantages and challenges, and propose corresponding improvement suggestions. The study employs methods such as literature review, interviews, and observations to conduct an in-depth analysis of blended learning practices in multiple higher vocational colleges. The research finds that blended learning models can enhance students’ learning motivation and teaching effectiveness, but there are still some issues in resource allocation, teacher training, and student adaptability. This paper suggests that higher vocational colleges should strengthen the construction of teaching resources, improve teachers’ information technology application capabilities, and optimize student learning support services to promote the in-depth development of blended learning models. The research results have significant reference value for the teaching reform and blended learning practice in higher vocational colleges.
Published in: International Journal of Research in Engineering, Science and Management (Volume 7, Issue 11, November 2024)
Page(s): 57-61
Date of Publication: 30/11/2024
Publisher: IJRESM
Cite as: Bin Xiao, Jialong Chen, Weijun He, “Research on the Current Situation, Advantages, and Challenges of Blended Learning Models in Higher Vocational Colleges,” in International Journal of Research in Engineering, Science and Management, vol. 7, no. 11, pp. 57-61, November 2024.